Estimação e mapeamento do nível de potência recebida do sinal digital de TV na região urbana da cidade de Mossoró – RN utilizando métodos de interpolação espacial

Abstract

The process of transitioning from the analog to the digital signal of the open television system is still in progress in Brazil. The analogue disconnection, which began in 2016 in the city of Rio Verde, in the state of Goiás (GO), is due to end on December 31, 2023. The city of Mossoró, in the state of Rio Grande do Norte (RN), had the analog signal completely turned off with the end of the first stage of the TV signal digitization process, on January 9, 2019. In this sense, the study of digital signal propagation is of great importance so that broadcasters can develop and improve the transmission service. This work aims to analyze the digital signal received power level of a TV station in the urban region of the city of Mossoró – RN. From a measurement campaign, real digital signal power data were compared with the reception threshold of – 77.40 dBm, established in the ABNT NBR 15604:2020 (Digital Terrestrial Television – Receivers) standard. At two points it was found that the received power was lower than the threshold, – 77.83 dBm and – 77.90 dBm. The greatest attenuation in these places may be related to the greater concentration of obstacles and agglomerations. In order to identify a more suitable propagation model for the studied environment, the collected data were compared with received power estimates calculated using different propagation models. Recommendation ITU-R P. 1546-6 provided the most accurate estimates based on the lowest values of Mean Absolute Error – MAE = 6.02 and Root Mean Squared Error – RMSE = 7.90. A good representation of the received power level contributes to the mapping of greater and lesser intensity of the digital signal in the region. To obtain continuous power data over the area of interest, different interpolation methods were used to generate spatial distribution maps of the digital signal in the urban region of Mossoró. The implementation of the interpolation methods was performed in Surfer® software (Golden Software, LLC), which provides the cross validation report with the Mean Error (ME) and RMSE values associated with each method. The lowest RMSE value (7.6083) indicated that the Ordinary Kriging method with exponential variogram model obtained the most accurate predictions